Probing metabolite diffusion at ultra‐short time scales in the mouse brain using optimized oscillating gradients and “short”‐echo‐time diffusion‐weighted MRS

Abstract

Measuring diffusion at ultra-short time scales may yield information about short-range intracellular structure and cytosol viscosity. However, reaching such time scales usually requires oscillating gradients, which in turn imply long echo times T . Here we propose a new kind of stretched oscillating gradient that allows us to increase diffusion-weighting b while preserving spectral and temporal properties of the gradient modulation. We used these optimized gradients to measure metabolite diffusion in the mouse brain down to effective diffusion times of 1 ms while keeping T relatively short (60 ms). At such T , a significant macromolecule signal could still be observed and used as an internal reference of approximately null diffusivity, which proved critical to discard datasets corrupted by some motion artifact. The methods introduced here may be useful to improve the accuracy and precision of metabolite apparent diffusion coefficient measurements with oscillating gradients.

Insights into brain microstructure from in vivo DW-MRS

“…The observed strong decrease in metabolite ADC as td is increased from ∼1 ms to ∼10 ms reported in (56,57) suggests that metabolite diffusion in brain cells is hindered by obstacles that are typically separated by distances of ≤2 μm. A priori, these obstacles could be either organelles or structures of the cytoskeleton, or simply the membranes of fibers extending from the cell bodies of neurons and glial cells, i.e.…”

“…LASER offers superior localization performance compared to STEAM or PRESS, as well as insensitivity to inhomogeneities of the radiofrequency making LASER a particularly attractive localization scheme, also for diffusionweighted MRS as pioneered in (55). In one variant, oscillating gradients were inserted around the first 180° refocusing pulse to measure metabolite diffusion at very short time scales (56,57). In another variant, three pairs of gradient pulses of opposite polarities were inserted around the three pairs of refocusing pulses to achieve single-shot isotropic diffusion-weighting while minimizing cross-terms with other gradients (58).…”

Validation of surface‐to‐volume ratio measurements derived from oscillating gradient spin echo on a clinical scanner using anisotropic fiber phantoms

“…For this project, we used an in‐house‐developed OGSE sequence. OGSE was performed using three different gradient waveforms: trapezoidal, cosine, and stretched cosine gradient with stretch factor 2. Non‐cosine gradient waveforms were implemented for increased b ‐value, while suppressing zero‐frequency lobes (Figure ).…”

Brain Metabolite Diffusion from Ultra-Short to Ultra-Long Time Scales: What Do We Learn, Where Should We Go?

“…They showed that ADC increased by ~50% when f increased from ~20 to 250 Hz for NAA, tCho, and tCr (also for Ins and Tau in the mouse brain), approaching ADC ~0.2–0.30 μm 2 /ms at the highest frequency. Note that, although later measurements in the mouse brain (Ligneul and Valette, 2017 ) suggested that early measurements in rats (Marchadour et al, 2012 ) may have been slightly biased by some motion artifact for some frequencies, the overall trend was preserved. The large ADC increase at short time-scales reflects significantly decreased restriction/hindrance and the progressive approach toward free diffusion.…”

“…To measure metabolite ADC at very short time-scales, experiments were performed in the rat (Marchadour et al, 2012 ) and mouse brain (Ligneul and Valette, 2017 ) using oscillating gradients. Measurements frequencies f went up to ~250 Hz, corresponding to diffusion time t d down to ~0.5–1 ms, depending on the conversion used between f and t d [ t d = 1/(4 f ) based on the identification of the effective diffusion time in the b -value expression (Parsons et al, 2006 ), or using t d = 9/(64 f ) as derived in the Mitra limit when considering the surface-to-volume ratio of the restrictions (Novikov and Kiselev, 2011 )].…”